What Python is | Python

Python is a general-purpose programming language used for scripting, data analysis, web backends, automation, machine learning, and much more. It is one of the most widely taught and widely used languages in the world.

What Python is used for

Python shows up in many different contexts:

Scripting and automation — writing small programs that rename files, scrape websites, send emails, or schedule tasks
Data analysis and visualization — loading datasets, cleaning data, computing statistics, and generating charts
Web backends — powering server-side logic with frameworks like Django, FastAPI, or Flask
Machine learning and AI — training models and running inference with libraries like PyTorch and TensorFlow
DevOps and infrastructure — writing deployment scripts, CI/CD tooling, and system administration utilities
Application development — building desktop tools, CLI utilities, and even games

The same core language underlies all of these. What changes is the ecosystem of libraries you use on top of it.

Where Python runs

Python runs on your local machine through a program called the Python interpreter. You install the interpreter once, and it can run any Python program you write.

Unlike JavaScript, which is embedded in browsers, Python is not built into your operating system by default. You install it separately. On most systems, the command python3 or python invokes the interpreter.

Interpreted vs compiled, at a useful level

Python is generally described as an interpreted language. When you run a Python file, the interpreter reads and executes it directly — there is no separate compilation step that produces a standalone binary.

Behind the scenes, Python does compile your code to an intermediate format called bytecode, which it then runs on a virtual machine. But you do not interact with this process directly. You write .py files and run them.

The practical difference from compiled languages like C or Go:

you write code and run it immediately
there is no compile step you need to manage
errors are discovered at runtime, not before the code runs
you can experiment interactively in a REPL (read-evaluate-print loop)

This makes Python fast to iterate on, which is one reason it is popular for exploration and prototyping.

Expressions vs statements

Python distinguishes between expressions and statements, just like most programming languages.

An expression produces a value:

2 + 3           # evaluates to 5
"hello".upper() # evaluates to "HELLO"
len([1, 2, 3])  # evaluates to 3

A statement performs an action. It may or may not produce a value:

x = 10          # assignment statement
print("hi")     # function call statement
if x > 5:       # conditional statement
    print(x)

The distinction matters because expressions can appear inside statements, but statements cannot appear inside expressions. You can write print(2 + 3) because 2 + 3 is an expression. You cannot write x = if True: 1 because if is a statement, not a value-producing expression.

Values vs variables

A value is a piece of data — a number, a string, a list, etc. A variable is a name that refers to a value.

count = 0

This does not mean “put 0 inside count.” It means “make the name count refer to the value 0.” If you later write count = 1, you are not changing the value 0 — you are making count refer to a different value.

This distinction becomes important when working with mutable data structures like lists and dictionaries, which you will encounter later.

What to carry forward

Python is a general-purpose language used for scripting, data, web, automation, and more
it runs through an interpreter that you install on your machine
code executes top to bottom, line by line
Python is dynamically typed — types are determined at runtime
expressions produce values; statements perform actions
variables are names that refer to values, not containers that hold them

The next lesson looks at how Python executes code in more detail and how to run Python programs.